Multidimensional Scaling (MDS) Computation

This documentation presents a detailed MATLAB source code implementation for Multidimensional Scaling (MDS) computation. The code implements classical MDS algorithm for dimensionality reduction of high-dimensional datasets, featuring eigenvalue decomposition of the distance matrix to preserve pairwise dissimilarities in lower-dimensional space. The implementation includes core functions for distance matrix calculation, double-centering transformation, and eigenvalue decomposition using MATLAB's built-in svd() function. The source code contains comprehensive inline comments explaining each algorithmic step and parameter configuration options for customized dimensionality reduction. Additionally, the package includes sample datasets and test cases demonstrating how to visualize high-dimensional data in 2D/3D space and validate the preservation of original data structure. The code architecture supports both metric and non-metric MDS variants, with modular functions for easy customization and integration into larger data analysis pipelines. This practical tool enables effective processing and analysis of high-dimensional data through robust mathematical implementation and user-friendly interface.